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#

flan-t5

Here are 140 public repositories matching this topic...

Swap GPT for any LLM by changing a single line of code. Xinference lets you run open-source, speech, and multimodal models on cloud, on-prem, or your laptop — all through one unified, production-ready inference API.

  • UpdatedFeb 20, 2026
  • Python

This repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5.

  • UpdatedJul 4, 2023
  • Python

[Preprint] Learning to Filter Context for Retrieval-Augmented Generaton

  • UpdatedApr 6, 2024
  • Python

LLMs4OL:‌ Large Language Models for Ontology Learning

  • UpdatedSep 27, 2024
  • Python

Official implementation of the paper "CoEdIT: Text Editing by Task-Specific Instruction Tuning" (EMNLP 2023)

  • UpdatedSep 23, 2024
  • Shell

[ACL 2024 Findings] Code implementation of Paper "Rethinking Negative Instances for Generative Named Entity Recognition"

  • UpdatedMar 20, 2024
  • Python

This repository contains the code to train flan t5 with alpaca instructions and low rank adaptation.

  • UpdatedJun 17, 2023
  • Python

Tools and our test data developed for the HackAPrompt 2023 competition

  • UpdatedOct 20, 2023
  • HTML

Empower your LLM to do more than you ever thought possible with these state-of-the-art prompt templates.

  • UpdatedSep 19, 2024
  • TypeScript

Fine-tuning of Flan-5T LLM for text classification 🤖 focuses on adapting a state-of-the-art language model to enhance its ability to classify text data.

  • UpdatedOct 28, 2024
  • Python

A template Next.js app for running language models like FLAN-T5 with Replicate's API

  • UpdatedMar 14, 2023
  • JavaScript

The TABLET benchmark for evaluating instruction learning with LLMs for tabular prediction.

  • UpdatedApr 28, 2023
  • Python

In this implementation, using the Flan T5 large language model, we performed the Text Classification task on the IMDB dataset and obtained a very good accuracy of 93%.

  • UpdatedMay 12, 2023
  • Jupyter Notebook

This project uses LLMs to generate music from text by understanding prompts, creating lyrics, determining genre, and composing melodies. It harnesses LLM capabilities to create songs based on text inputs through a multi-step approach.

  • UpdatedMay 21, 2024
  • Jupyter Notebook

Use AI to personify books, so that you can talk to them 🙊

  • UpdatedMar 25, 2023
  • Jupyter Notebook

Training and fine-tuning flan-t5-small model based on provided text

  • UpdatedJul 18, 2024
  • Python

In-context learning, Fine-Tuning, RLHF on Flan-T5

  • UpdatedAug 30, 2023
  • Jupyter Notebook

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